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Use Dash to Build to Web Apps on SendGrid Data

The CData Python Connector for SendGrid enables you to create Python applications that use pandas and Dash to build SendGrid-connected web apps.

The rich ecosystem of Python modules lets you get to work quickly and integrate your systems more effectively. With the CData Python Connector for SendGrid, the pandas module, and the Dash framework, you can build SendGrid-connected web applications for SendGrid data. This article shows how to connect to SendGrid with the CData Connector and use pandas and Dash to build a simple web app for visualizing SendGrid data.

With built-in, optimized data processing, the CData Python Connector offers unmatched performance for interacting with live SendGrid data in Python. When you issue complex SQL queries from SendGrid, the driver pushes supported SQL operations, like filters and aggregations, directly to SendGrid and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).

Connecting to SendGrid Data

Connecting to SendGrid data looks just like connecting to any relational data source. Create a connection string using the required connection properties. For this article, you will pass the connection string as a parameter to the create_engine function.

To make use of all the available features, provide the User and Password connection properties.

To connect with limited features, you can set the APIKey connection property instead. See the "Getting Started" chapter of the help documentation for a guide to obtaining the API key.

After installing the CData SendGrid Connector, follow the procedure below to install the other required modules and start accessing SendGrid through Python objects.

Install Required Modules

Use the pip utility to install the required modules and frameworks:

pip install pandas
pip install dash
pip install dash-daq

Visualize SendGrid Data in Python

Once the required modules and frameworks are installed, we are ready to build our web app. Code snippets follow, but the full source code is available at the end of the article.

First, be sure to import the modules (including the CData Connector) with the following:

import os
import dash
import dash_core_components as dcc
import dash_html_components as html
import pandas as pd
import cdata.sendgrid as mod
import plotly.graph_objs as go

You can now connect with a connection string. Use the connect function for the CData SendGrid Connector to create a connection for working with SendGrid data.

cnxn = mod.connect("User=admin;Password=abc123;")

Execute SQL to SendGrid

Use the read_sql function from pandas to execute any SQL statement and store the result set in a DataFrame.

df = pd.read_sql("SELECT Name, Clicks FROM AdvancedStats WHERE Type = 'Device'", cnxn)

Configure the Web App

With the query results stored in a DataFrame, we can begin configuring the web app, assigning a name, stylesheet, and title.

app_name = 'dash-sendgridedataplot'

external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']

app = dash.Dash(__name__, external_stylesheets=external_stylesheets)
app.title = 'CData + Dash'

Configure the Layout

The next step is to create a bar graph based on our SendGrid data and configure the app layout.

trace = go.Bar(x=df.Name, y=df.Clicks, name='Name')

app.layout = html.Div(children=[html.H1("CData Extension + Dash", style={'textAlign': 'center'}),
	dcc.Graph(
		id='example-graph',
		figure={
			'data': [trace],
			'layout':
			go.Layout(title='SendGrid AdvancedStats Data', barmode='stack')
		})
], className="container")

Set the App to Run

With the connection, app, and layout configured, we are ready to run the app. The last lines of Python code follow.

if __name__ == '__main__':
    app.run_server(debug=True)

Now, use Python to run the web app and a browser to view the SendGrid data.

python sendgrid-dash.py

Free Trial & More Information

Download a free, 30-day trial of the SendGrid Python Connector to start building Python apps with connectivity to SendGrid data. Reach out to our Support Team if you have any questions.



Full Source Code

import os
import dash
import dash_core_components as dcc
import dash_html_components as html
import pandas as pd
import cdata.sendgrid as mod
import plotly.graph_objs as go

cnxn = mod.connect("User=admin;Password=abc123;")

df = pd.read_sql("SELECT Name, Clicks FROM AdvancedStats WHERE Type = 'Device'", cnxn)
app_name = 'dash-sendgriddataplot'

external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']

app = dash.Dash(__name__, external_stylesheets=external_stylesheets)
app.title = 'CData + Dash'
trace = go.Bar(x=df.Name, y=df.Clicks, name='Name')

app.layout = html.Div(children=[html.H1("CData Extension + Dash", style={'textAlign': 'center'}),
	dcc.Graph(
		id='example-graph',
		figure={
			'data': [trace],
			'layout':
			go.Layout(title='SendGrid AdvancedStats Data', barmode='stack')
		})
], className="container")

if __name__ == '__main__':
    app.run_server(debug=True)